An infectious way to teach students about outbreaks

Autor: Íde Cremin, Oliver Watson, Alastair Heffernan, Natsuko Imai, Norin Ahmed, Sandra Bivegete, Teresia Kimani, Demetris Kyriacou, Preveina Mahadevan, Rima Mustafa, Panagiota Pagoni, Marisa Sophiea, Charlie Whittaker, Leo Beacroft, Steven Riley, Matthew C. Fisher
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: Epidemics, Vol 23, Iss , Pp 42-48 (2018)
Druh dokumentu: article
ISSN: 1755-4365
DOI: 10.1016/j.epidem.2017.12.002
Popis: The study of infectious disease outbreaks is required to train today’s epidemiologists. A typical way to introduce and explain key epidemiological concepts is through the analysis of a historical outbreak. There are, however, few training options that explicitly utilise real-time simulated stochastic outbreaks where the participants themselves comprise the dataset they subsequently analyse. In this paper, we present a teaching exercise in which an infectious disease outbreak is simulated over a five-day period and subsequently analysed. We iteratively developed the teaching exercise to offer additional insight into analysing an outbreak. An R package for visualisation, analysis and simulation of the outbreak data was developed to accompany the practical to reinforce learning outcomes. Computer simulations of the outbreak revealed deviations from observed dynamics, highlighting how simplifying assumptions conventionally made in mathematical models often differ from reality. Here we provide a pedagogical tool for others to use and adapt in their own settings. Keywords: Teaching, Outbreak analysis, Pedagogical tool, Simulation analysis, Network reconstruction
Databáze: Directory of Open Access Journals